# MQL5 Freelance Jobs Monitor — Low-Competition Job Finder (`nick.i/mql5-freelance-jobs`) Actor Monitors the public MQL5 Freelance job board (EA and indicator development gigs, budgets in escrow) and returns structured job data with an opportunity score: budget range, number of applicants, required skills, posting time. Schedule it to catch low-competition jobs minutes after they are posted. - **URL**: https://apify.com/nick.i/mql5-freelance-jobs.md - **Developed by:** [Nick Illig](https://apify.com/nick.i) (community) - **Categories:** Jobs, Automation - **Stats:** 2 total users, 0 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing Pay per usage This Actor is paid per platform usage. The Actor is free to use, and you only pay for the Apify platform usage, which gets cheaper the higher subscription plan you have. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-usage ## What's an Apify Actor? Actors are a software tools running on the Apify platform, for all kinds of web data extraction and automation use cases. In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours, and optionally produces a well-defined JSON output, datasets with results, or files in key-value store. In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server. Actors are written with capital "A". ## How to integrate an Actor? If asked about integration, you help developers integrate Actors into their projects. You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready. The best way to integrate Actors is as follows. In JavaScript/TypeScript projects, use official [JavaScript/TypeScript client](https://docs.apify.com/api/client/js.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python.md): ```bash pip install apify-client ``` In shell scripts, use [Apify CLI](https://docs.apify.com/cli/docs.md): ````bash # MacOS / Linux curl -fsSL https://apify.com/install-cli.sh | bash # Windows irm https://apify.com/install-cli.ps1 | iex ```bash In AI frameworks, you might use the [Apify MCP server](https://docs.apify.com/platform/integrations/mcp.md). If your project is in a different language, use the [REST API](https://docs.apify.com/api/v2.md). For usage examples, see the [API](#api) section below. For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt). # README ## MQL5 Freelance Jobs Monitor — Low-Competition Job Finder Monitors the **public MQL5 Freelance job board** — the escrow-backed marketplace where traders hire developers for Expert Advisors, indicators and MQL4→MQL5 conversions — and returns structured job data **with an opportunity score**. ### Why this is useful On MQL5 Freelance, speed wins: small, clearly-specified jobs often get taken within hours by the first credible applicant. This Actor lets you: - **Catch low-competition jobs early** — schedule it every 15-30 minutes and filter for `verdict: HOT` (sweet-spot budget, ≤2 applicants, clear scope). - **Feed alerts** — combine with Apify integrations (Slack, email, webhooks) to get pinged the moment a good job appears. - **Analyze the market** — budgets, in-demand skills, posting volume over time. ### Output fields | Field | Example | |---|---| | `jobId` / `url` | `250363` / `https://www.mql5.com/en/job/250363` | | `title` | `Add EMA trend filter to existing EA` | | `budgetMin` / `budgetMax` / `currency` | `30` / `50` / `USD` | | `applications` | `2` | | `language` | `MQL5` | | `categories` / `skills` | `["Experts"]` / `["Strategy optimization"]` | | `postedAt` | `2026-07-05T18:38Z` | | `opportunityScore` / `verdict` | `7` / `HOT` | | `scoreReasons` | `["budget 30-50 in sweet spot", "low competition (2 applicants)"]` | ### Scoring logic Configurable via input: sweet-spot budget range (default $30-100), low-competition threshold (default ≤2 applicants). Bonus for clear-scope keywords (fix, convert, alert, trailing, prop firm …), penalty for red flags (martingale / "never loses" fantasies) and very thin specs. ### Fair use Reads public listing pages only, 1 request / 2 seconds, no login, no personal data beyond public job postings. # Actor input Schema ## `maxPages` (type: `integer`): Listing pages to fetch (20 jobs per page, newest first) ## `includePersonalJobs` (type: `boolean`): Personal jobs are direct-hire postings you cannot bid on; excluded by default ## `sweetBudgetMin` (type: `integer`): Lower bound of the budget range considered ideal for the opportunity score ## `sweetBudgetMax` (type: `integer`): Upper bound of the ideal budget range ## `maxApplications` (type: `integer`): Jobs with at most this many applicants are scored as low-competition ## `proxyConfiguration` (type: `object`): Proxy settings; Apify proxy is recommended ## Actor input object example ```json { "maxPages": 3, "includePersonalJobs": false, "sweetBudgetMin": 30, "sweetBudgetMax": 100, "maxApplications": 2, "proxyConfiguration": { "useApifyProxy": true } } ```` # API You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup. ## JavaScript example ```javascript import { ApifyClient } from 'apify-client'; // Initialize the ApifyClient with your Apify API token // Replace the '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = { "proxyConfiguration": { "useApifyProxy": true } }; // Run the Actor and wait for it to finish const run = await client.actor("nick.i/mql5-freelance-jobs").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`); const { items } = await client.dataset(run.defaultDatasetId).listItems(); items.forEach((item) => { console.dir(item); }); // 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs ``` ## Python example ```python from apify_client import ApifyClient # Initialize the ApifyClient with your Apify API token # Replace '' with your token. client = ApifyClient("") # Prepare the Actor input run_input = { "proxyConfiguration": { "useApifyProxy": True } } # Run the Actor and wait for it to finish run = client.actor("nick.i/mql5-freelance-jobs").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print("💾 Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"]) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) # 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{ "proxyConfiguration": { "useApifyProxy": true } }' | apify call nick.i/mql5-freelance-jobs --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=nick.i/mql5-freelance-jobs", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "MQL5 Freelance Jobs Monitor — Low-Competition Job Finder", "description": "Monitors the public MQL5 Freelance job board (EA and indicator development gigs, budgets in escrow) and returns structured job data with an opportunity score: budget range, number of applicants, required skills, posting time. Schedule it to catch low-competition jobs minutes after they are posted.", "version": "0.1", "x-build-id": "d0E8OmfEql1TyIdGV" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/nick.i~mql5-freelance-jobs/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-nick.i-mql5-freelance-jobs", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/nick.i~mql5-freelance-jobs/runs": { "post": { "operationId": "runs-sync-nick.i-mql5-freelance-jobs", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/nick.i~mql5-freelance-jobs/run-sync": { "post": { "operationId": "run-sync-nick.i-mql5-freelance-jobs", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } } }, "components": { "schemas": { "inputSchema": { "type": "object", "properties": { "maxPages": { "title": "Max pages", "minimum": 1, "maximum": 30, "type": "integer", "description": "Listing pages to fetch (20 jobs per page, newest first)", "default": 3 }, "includePersonalJobs": { "title": "Include personal jobs", "type": "boolean", "description": "Personal jobs are direct-hire postings you cannot bid on; excluded by default", "default": false }, "sweetBudgetMin": { "title": "Sweet-spot budget min (USD)", "minimum": 0, "type": "integer", "description": "Lower bound of the budget range considered ideal for the opportunity score", "default": 30 }, "sweetBudgetMax": { "title": "Sweet-spot budget max (USD)", "minimum": 1, "type": "integer", "description": "Upper bound of the ideal budget range", "default": 100 }, "maxApplications": { "title": "Max applicants for low competition", "minimum": 0, "type": "integer", "description": "Jobs with at most this many applicants are scored as low-competition", "default": 2 }, "proxyConfiguration": { "title": "Proxy configuration", "type": "object", "description": "Proxy settings; Apify proxy is recommended", "default": { "useApifyProxy": true } } } }, "runsResponseSchema": { "type": "object", "properties": { "data": { "type": "object", "properties": { "id": { "type": "string" }, "actId": { "type": "string" }, "userId": { "type": "string" }, "startedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "finishedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "status": { "type": "string", "example": "READY" }, "meta": { "type": "object", "properties": { "origin": { "type": "string", "example": "API" }, "userAgent": { "type": "string" } } }, "stats": { "type": "object", "properties": { "inputBodyLen": { "type": "integer", "example": 2000 }, "rebootCount": { "type": "integer", "example": 0 }, "restartCount": { "type": "integer", "example": 0 }, "resurrectCount": { "type": "integer", "example": 0 }, "computeUnits": { "type": "integer", "example": 0 } } }, "options": { "type": "object", "properties": { "build": { "type": "string", "example": "latest" }, "timeoutSecs": { "type": "integer", "example": 300 }, "memoryMbytes": { "type": "integer", "example": 1024 }, "diskMbytes": { "type": "integer", "example": 2048 } } }, "buildId": { "type": "string" }, "defaultKeyValueStoreId": { "type": "string" }, "defaultDatasetId": { "type": "string" }, "defaultRequestQueueId": { "type": "string" }, "buildNumber": { "type": "string", "example": "1.0.0" }, "containerUrl": { "type": "string" }, "usage": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "integer", "example": 1 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } }, "usageTotalUsd": { "type": "number", "example": 0.00005 }, "usageUsd": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "number", "example": 0.00005 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } } } } } } } } } ```